纯Go中的图像处理算法_Go_下载.zip

# bild  [](https://github.com/anthonynsimon/bild/blob/master/LICENSE) [](https://godoc.org/github.com/anthonynsimon/bild) [](https://goreportcard.com/report/github.com/anthonynsimon/bild) A collection of parallel image processing algorithms in pure Go. The aim of this project is simplicity in use and development over absolute high performance, but most algorithms are designed to be efficient and make use of parallelism when available. It uses packages from the standard library whenever possible to reduce dependency use and development abstractions. All operations return image types from the standard library. ## Documentation The documentation for the various packages is available [here](https://pkg.go.dev/mod/github.com/anthonynsimon/bild?tab=packages). ## CLI usage Download and compile from sources: ``` go get github.com/anthonynsimon/bild ``` Or get the pre-compiled binaries for your platform on the [releases page](https://github.com/anthonynsimon/bild/releases) ``` bild A collection of parallel image processing algorithms in pure Go Usage: bild [command] Available Commands: adjust adjust basic image features like brightness or contrast blend blend two images together blur blur an image using the specified method channel channel operations on images effect apply effects on images help Help about any command histogram histogram operations on images imgio i/o operations on images noise noise generators segment segment an image using the specified method Flags: -h, --help help for bild --version version for bild Use "bild [command] --help" for more information about a command. ``` For example, to apply a median effect with a radius of 1.5 on the image `input.png`, writing the result into a new file called `output.png`: ``` bild effect median --radius 1.5 input.png output.png ``` ## Install package bild requires Go version 1.11 or greater. ```bash go get github.com/anthonynsimon/bild/... ``` ## Basic package usage example: ```go package main import ( "github.com/anthonynsimon/bild/effect" "github.com/anthonynsimon/bild/imgio" "github.com/anthonynsimon/bild/transform" ) func main() { img, err := imgio.Open("input.jpg") if err != nil { fmt.Println(err) return } inverted := effect.Invert(img) resized := transform.Resize(inverted, 800, 800, transform.Linear) rotated := transform.Rotate(resized, 45, nil) if err := imgio.Save("output.png", rotated, imgio.PNGEncoder()); err != nil { fmt.Println(err) return } } ``` # Output examples ## Adjustment import "github.com/anthonynsimon/bild/adjust" ### Brightness result := adjust.Brightness(img, 0.25)  ### Contrast result := adjust.Contrast(img, -0.5)  ### Gamma result := adjust.Gamma(img, 2.2)  ### Hue result := adjust.Hue(img, -42)  ### Saturation result := adjust.Saturation(img, 0.5)  ## Blend modes import "github.com/anthonynsimon/bild/blend" result := blend.Multiply(bg, fg) | Add | Color Burn | Color Dodge | | :----------: | :---------: | :------: | |  |  |  | | **Darken** | **Difference** | **Divide** | |  |  |  | | **Exclusion** | **Lighten** | **Linear Burn** | |  |  |  | | **Linear Light** | **Multiply** | **Normal** | |  |  |  | | **Opacity** | **Overlay** | **Screen** | |  |  |  | | **Soft Light** | **Subtract** | | |  |  | | ## Blur import "github.com/anthonynsimon/bild/blur" ### Box Blur result := blur.Box(img, 3.0)  ### Gaussian Blur result := blur.Gaussian(img, 3.0)  ## Channel import "github.com/anthonynsimon/bild/channel" ### Extract Channels result := channel.Extract(img, channel.Alpha)  ### Extract Multiple Channels result := channel.ExtractMultiple(img, channel.Red, channel.Alpha) ## Effect import "github.com/anthonynsimon/bild/effect" ### Dilate result := effect.Dilate(img, 3)  ### Edge Detection result := effect.EdgeDetection(img, 1.0)  ### Emboss result := effect.Emboss(img)  ### Erode result := effect.Erode(img, 3)  ### Grayscale result := effect.Grayscale(img)  ### Invert result := effect.Invert(img)  ### Median result := effect.Median(img, 10.0)  ### Sepia result := effect.Sepia(img)  ### Sharpen result := effect.Sharpen(img)  ### Sobel result := effect.Sobel(img)  ### Unsharp Mask result := effect.UnsharpMask(img, 0.6, 1.2)  ## Histogram import "github.com/anthonynsimon/bild/histogram" ### RGBA Histogram hist := histogram.NewRGBAHistogram(img) result := hist.Image()  ## Noise import "github.com/anthonynsimon/bild/noise" ### Uniform colored result := noise.Generate(280, 280, &noise.Options{Monochrome: false, NoiseFn: noise.Uniform})  ### Binary monochrome result := noise.Generate(280, 280, &noise.Options{Monochrome: true, NoiseFn: noise.Binary})  ### Gaussian monochrome result := noise.Generate(280, 280, &noise.Options{Monochrome: true, NoiseFn: noise.Gaussian})  ### Perlin Noise result := noise.GeneratePerlin(280, 280, 0.25)  ## Paint import "github.com/anthonynsimon/bild/paint" ### Flood Fill // Fuzz is the percentage of maximum color distance that is tolerated result := paint.FloodFill(img, image.Point{240, 0}, color.RGBA{255, 0, 0, 255}, 15)  ## Segmentation import "github.com/anthonynsimon/bild/segment" ### Threshold result := segment.Threshold(img, 128)  ## Transform import "github.com/anthonynsimon/bild/transform" ### Crop // Source image is 280x280 result := transform.Crop(img, image.Rect(70,70,210,210))  ### FlipH result := transform.FlipH(img)  ### FlipV result := transform.FlipV(img)  ### Resize Resampling Filters result := transform.Resize(img, 280, 280, transform.Linear) | Nearest Neighbor | Linear | Gaussian | |:----------: | :---------: | :------: | |  |  |  | | **Mitchell Netravali** | **Catmull Rom** | **Lanczos** | | ![](assets/img/resizem